Adaptive range selection for parameter optimization of VMD algorithm in rolling bearing fault diagnosis under strong background noise
Author:
Publisher
Springer Science and Business Media LLC
Subject
Mechanical Engineering,Mechanics of Materials
Link
https://link.springer.com/content/pdf/10.1007/s12206-023-1015-3.pdf
Reference44 articles.
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3. R.-B. Sun, Z.-B. Yang, Z. Zhai and X.-F. Chen, Sparse representation based on parametric impulsive dictionary design for bearing fault diagnosis, Mechanical Systems and Signal Processing, 122 (2019) 737–753.
4. B. Chen et al., Integrated early fault diagnosis method based on direct fast iterative filtering decomposition and effective weighted sparseness kurtosis to rolling bearings, Mechanical Systems and Signal Processing, 171 (2023) 108897.
5. Y. Guo, Y. Bao, H. Li and Y. Zhang, Deep learning-based adaptive mode decomposition and instantaneous frequency estimation for vibration signal, Mechanical Systems and Signal Processing, 199 (2023) 110463.
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